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dVQA: Using Data to Detect Video Quality Issues Economically at Scale
Live streaming runs 24/7, necessitating round-the-clock monitoring. However, VQA monitoring is highly resource-intensive. Fortunately, data-driven methods offer a more economic alternative to hardware, drastically reducing costs. Touchstream’s dVQA leverages existing data from Touchstream’s ABR monitoring, employing a machine learning approach to predict potential VQ issues. vvvv
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AI – Tutorial, Ep 2 – The AI Implementation Compass: Going from innovation to transformation
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